This paper studies the product language construction of the twisted porcelain cultural heritage. Through field research, we collected and sorted out samples of twisted porcelain products, explored the product language characteristics of twisted porcelain from multiple aspects such as production process, product shape, and product color, interpreted cultural value, captured potential connotations, extracted representative words from user comments, quantified the relationship between users and twisted porcelain culture, realized the construction and transmission of traditional cultural language information, conveyed the traditional cultural information of the product to users, and promoted the sustainable dissemination and development of this cultural heritage. The research results show that after mining and extraction at the level of twisted porcelain characteristics, the core language constructs the cultural expression of twisted porcelain products, which is more in line with the needs of the market and users, and has the potential to be developed and disseminated using the language generation of cultural heritage products.

Improving the practical skills of Science, Technology, Engineering and Mathematics (STEM) students at a historically black college and university (HBCU) was done by implementing a transformative teaching model. The model was implemented on undergraduate students of different educational levels in the Electrical Engineering (EE) Department at HBCU. The model was also extended to carefully chosen high and middle schools. These middle and high school students serve as a pipeline to the university, with a particular emphasis on fostering growth within the EE Department. The model aligns well with the core mission of the EE Department, aiming to enhance the theoretical knowledge and practical skills of students, ensuring that they are qualified to work in industry or to pursue graduate studies. The implemented model prepares students for outstanding STEM careers. It also increases enrolment, student retention, and the number of underrepresented minority graduates in a technology-based workforce.

The Three Kingdoms period of ancient China (208-280 AD) refers to the period  between Eastern Han (25–220 AD) and Jin dynasties (266–420), during which China was divided into Shu (221-263 AD), Wei  (220-266 AD) and Wu (222-280 AD) kingdoms, and then united as Jin dynasty. This paper constructs the quarterly series of alliance structures between the Three Kingdoms. By collecting and analyzing a total of two hundred and eighty-nine quarterly observations, the paper shows that the three most frequent alliance structures are ρ0: 1) the finest partition or no-alliance structure with 192 partitions; 2) Three partitions with Shu-Jin alliance and Wu singletion with 57 partions; 3) Wei-Wu alliance and one singletion Shu with 12 partions. It also shows that the observed changes in alliance structures were the consequence of a total of fifteen major battles fought by the three kingdoms. Such results serve as a contribution to the studies of applied game theory, alliance study, and the economic and military histories in ancient China.

This study offers a new perspective on measuring the impact of village funds (DD) on rural development. Using a mixed-method approach, the qualitative analysis reveals that, like previous rural development programs, the DD program struggles to implement inclusive methods for capturing community aspirations and evaluating outcomes. Despite rural infrastructure improvement, many villagers feel they have not fully benefited and do not view it as offering economic opportunities. The econometric model confirms the qualitative findings, indicating no significant DD influence on the village development index (IPD). Instead, effective governance factors like Musdes, regulations, and leadership are essential for the IPD improvement. Thus, enhancing village governments’ institutional capacity is crucial for increasing the DD effectiveness. The paper recommends several measures: training village officials in financial management and project planning, providing guidelines for the DD allocation and usage, creating robust monitoring-evaluation systems, developing communication strategies, and fostering partnerships with local NGOs and universities.

Social Services are vital for addressing adversity and safeguarding vulnerable individuals, presenting professionals with complex challenges that demand resilience, recovery, and continual learning. This study investigates Organizational Resilience within Community Social Services, focusing on strategic planning, adaptive capacity, and user perspectives. A cross-sectional study involved 534 professionals and service users from Community Social Services Centers in Spain. Centers were selected based on the characteristics of their population and the representativeness of their geographic location. The study utilized the Benchmark Resilience Tool (BRT) to evaluate Organizational Resilience and the SERVPERF questionnaire to gauge user-perceived service quality. The results demonstrate satisfactory levels of Organizational Resilience and user satisfaction, while also highlighting key areas for enhancing resilient strategies: reinforcement of personnel for thinking outside the box or in the resources available to the organization to face unexpected changes. These findings suggest the need to develop and optimize measures that improve the organization’s ability to adapt to and recover from adverse situations, ensuring a positive user experience. Emphasizing the importance of resilience in Social Services as a quality predictor, future research should explore innovative strategies to bolster Organizational Resilience. The findings emphasize the need to strengthen resilience in Social Services, enhancing practice, policy, and adaptability to support vulnerable populations.

Purpose: This research examines the intricate interplay between Business Intelligence (BI), Big Data Analytics (BDA), and Artificial Intelligence (AI) within the realm of Supply Chain Management (SCM). While the integration of these technologies has promised improved operational efficiency and decision-making capabilities, concerns about complexities and potential overreliance on technology persist. The study aims to provide insights into achieving a balance between data-driven insights and qualitative factors in SCM for sustained competitiveness. Design/methodology/approach: The research executed interviews with ten Arab Gulf-based consulting firms. These companies’ ability to successfully complete BI projects is well recognised. Findings: Through examining the interplay of human judgement and data-driven strategies, addressing integration challenges, and understanding the risks of excessive data reliance, the research enhances comprehension of the modern SCM landscape. It underscores BI’s foundational role, the necessity of balanced human input, and the significance of customer-centric strategies for lasting competitive advantage and relationships. Practical implications: The research provided information for organizations seeking to effectively navigate the complexities of integrating data-driven technologies in SCM. The research is a foundation for future studies to delve deeper into quantitative measurement methodologies and effective data security strategies in the SCM context. Originality: The research highlights the value of integrating BI, BDA, and AI in SCM for improved efficiency, cost reduction, and customer satisfaction, emphasising the need for a balanced approach that combines data-driven insights, human judgement, and customer-centric strategies to maintain competitiveness.